Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Second hand smoke exposure in workplace by job status and occupations

Second hand smoke exposure in workplace by job status and occupations Background: The objective of this study is to evaluate the risk of exposure to second hand smoke (SHS) during working hours by job status and occupation. Methods: Using the 4th Korean Working Conditions Survey (KWCS), 49,674 respondents who answered the question about SHS were studied. A chi-square test was carried out to determine whether there is a significant different in SHS exposure frequency by general and occupational characteristics and experience of discrimination at work and logistic regression analysis was carried out to identify the risk level of SHS exposure by variables. Results: In this study, we found that male workers in their 40s and 50s, workers employed in workplaces with fewer than 50 employees, daily workers, and people working outdoors had a higher rate of exposure to SHS than the others. The top five occupations with the highest SHS exposure were construction and mining-related occupations, metal core-makers-related trade occupations, wood and furniture, musical instrument, and signboard- related trade occupations, transport and machine-related trade occupations, transport and leisure services occupations. The least five exposed occupations were public and enterprise senior officers, legal and administrative professions, education professionals, and health, social welfare, and religion-related occupations. Conclusion: Tobacco smoke is a significant occupational hazard. Smoking ban policy in the workplace can be a very effective way to reduce the SHS exposure rate in the workplace and can be more effective if specifically designed by the job status and various occupations. Keywords: Second hand smoke exposure, Job status, Occupations, Smoking ban Background smoking rate for Korean males aged more than 15 was Second hand smoke (SHS), which is exposure to smoke 31.4% as of 2015, which was the third highest rank among from cigarette butts or smoke exhaled by smokers, is OECD countries. The Korean government has imple- itself a Group 1 carcinogen for the human as classified mented a policy of smoking bans in public places for by the International Agency for Research on Cancer many years, but that smoking policy only applies with a (IARC). Exposure to SHS is known to be associated with workplace more than 1000 m in total area [4]. For that respiratory and cardiovascular diseases as well as anxiety reason, the workplace is still at a high rate of SHS expos- disorders, mental health, and psychological stress [1]. ure and could be the environment that can be improved According to the National Health Statistics in Korea for further in SHS exposure reduction. 2015 [2], the current indoor SHS exposure rate of non- From 1999 to 2002 US NHANES (National Health smokers at work was 26.8%, remarkably high compared and Nutrition Examination Survey) data, there have with at home, which is 8.2%. From OECD (Organization been dramatic reduction in the serum cotinine levels for Economic Cooperation and Development) data [3], the caused by successful smoking-free laws [5]. Although SHS exposure rates are declining, the workplace remains a significant source of SHS exposure [6, 7]. Working * Correspondence: bioaerosol@kosha.or.kr Work Environment Research Bureau, Occupational Safety and Health adults spend most of their time at workplace and for Research Institute, 400, Jongga-ro, Jung-gu, Ulsan, Republic of Korea those non-smokers, the workplace may be the major Department of Public Health Science, Graduate School of Public Health, and source of provider to SHS exposure [8]. In the German Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 2 of 9 study, More than 40% of non-smokers reported experi- (ESQ rate) was used to compare the SHS exposure by encing SHS at work [9]. Workplace smoking is an occupa- independent variables. tional health hazard and a smoking ban policy at the Independent variables included information on gender workplace is the best option to reduce SHS [10]. More (“male” and “female”), age group ( “≤ 39”, “40–49”, “50–59” than 50% of European countries enforce non-smoking and “≥ 60”), job status (“self-employed without workers”, regulations at work and the other European countries also “self-employed with workers”, “wage workers (employees)”, partially restrict smoking at work. In the Netherlands, the “unpaid family worker” and “other workers”), type of wage comparison of SHS exposure rates before and after the worker (“permanent workers”, “temporary workers” and implementation of the smoking ban policy in the work- “daily workers”), wage provider (“workplace”, “adispatcher” place showed that the SHS exposure rate decreased from and “service provider”), Companysizeas numberof 70.7 to 51.9%. However, the rate of SHS exposure is still workers in workplace ( “≤ 49”, “50–299” and “≥ 300”), type high in the Netherlands even after the smoking ban at of workplace (“employer’s place of business”, “customer’s work, because of a high-risk group for smoking such as place of business”, “in the case of transportation as cars”, males and low-educated workers [11]. “outdoor (construction, field/etc)”, “my home” and To reinforce the appropriated non-smoking policy at “others”), job category (“manager”, “specialist”, “technician workplace, it is important to identify priority group to and associate export”, “office worker”, “service worker”, implement such as vulnerable job status and occupations “sales worker”, “experts in agriculture and forestry fishing”, to SHS exposure. In this study, we evaluated the risk of “functional person and related person”, “machine operator exposure to tobacco smoke by others during working and assembly worker”, “laborer” and “soldier”), and night hours by job status, experience of discrimination at work working days in a month ( “≤ 9”, “10–19” and “≥ 20”). and occupation using the data of the 4th Korean Work- The item designed to evaluate the experience of dis- ing Conditions Survey (KWCS). crimination at the workplace was used as a variables for the effect of exposure to SHS. The question is “During the past 12 months, did you experience to discrimin- Methods ation at your workplace related to age, race, nationality, Study subjects gender, religion, disability, sexual orientation, academic This study used data from the 4th Korean Working Con- group, region of origin, or employment status?” Respon- ditions Survey (KWCS), which was conducted between dents answered to the question about discrimination June and September 2014 on employed workers by the with ‘yes’ or ‘no’. Occupational Safety and Health Research Institute The occupational categories of respondents were clas- (OSHRI) affiliated under the Ministry of Employment and sified according to the Korean Standard Classification of Labor. The KWCS selected individuals who satisfied cri- Occupation (KSCO by National Statistical Office) and teria for the definition of “economically active population” classified into occupational groups (52 groups, classifica- conducted one-on-one interviews at their home by a pro- tion code: 2 digits) and detailed occupation (415 groups, fessional interviewer. The total sample of 50,007 persons, classification code: 4 digits). 15 years or older participated in this survey. The data used in this study are from 49,674 respondents who answered Statistical analysis the question “Are you exposed at work to tobacco smoke Data were analyzed using PASW version 18.0 (SPSS Inc., from other people?” Chicago, IL, USA). Weight is applied when conducting statistical analysis based on the results of the “economic- Variables selected for analysis ally active population survey (EAPS)” in 2014 conducted The dependent variable was assessed to evaluate the risk by National Statistical Office. A chi-square test was of exposure to SHS by a question, “Are you exposed at carried out to determine whether there is a significant work to tobacco smoke from other people?” Respon- different between SHS exposure frequency by general dents answered on a seven-point scale of SHS exposure and occupational characteristics and experience of frequency; the choices were (in terms of all of the work- discrimination at work and logistic regression analysis ing time), “all”, “almost”, “3/4”, “half”, “1/4”, “almost was carried out to identify the risk level of SHS exposure never”, and “never”. For chi-square test, exposure to by variables. SHS in workplace was categorized into 3 group; “over 1/ 4 workhours” (all ~ 1/4), “almost never” and “never”. For Results logistic regression exposure to SHS in workplace was General characteristics of population categorized into 2 group; “over 1/4 workhours” (all ~ 1/ The sample characteristics are described in Table 1.Of 4) or “less than 1/4” (almost never and never). The rate the total 49,674 respondents, 57.8% were male and of exposure to SHS for more than 1/4 of workhours 36.9% were under the age of 39 which was the largest Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 3 of 9 Table 1 General characteristics of the study subjects Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Gender Male 28,732 (57.8%) 4587 (16.0) 9163 (31.9) 14,982 (52.1) p < 0.01 Female 20,942 (42.2%) 1441 (6.9) 5939 (28.4) 13,562 (64.8) Age(yrs) ≤ 39 18,351 (36.9%) 1661 (9.1) 5341 (29.1) 11,349 (61.8) p < 0.01 40–49 12,958 (26.1%) 1777 (13.7) 3929 (30.3) 7252 (56.0) 50–59 11,348 (22.8%) 1698 (15.0) 3608 (31.8) 6042 (53.2) ≥ 60 7017 (14.1%) 892 (12.7) 2224 (31.7) 3901 (55.6) Job status Self-employed without workers 8058 (16.2%) 915 (11.4) 2449 (30.4) 4694 (58.3) p < 0.01 Self-employed with workers 3012 (6.1%) 522 (17.3) 913 (30.3) 1577 (52.4) Wage workers (employees) 36,156 (72.8%) 4344 (12.0) 10,956 (30.3) 20,856 (57.7) Unpaid family worker 2417 (4.9%) 244 (10.1) 767 (31.7) 1406 (58.2) Other workers 27 (0.1%) 3 (11.1) 14 (51.9) 10 (37.0) Type of wage workers Permanent workers 27,279 (76.0%) 2900 (10.6) 8459 (31.0) 15,920 (58.4) p < 0.01 Temporary workers 6083 (16.9%) 722 (11.9) 1709 (28.1) 3652 (60.0) Daily workers 2551 (7.1%) 675 (26.5) 716 (28.1) 1160 (45.5) Wage_provider Work place 33,503 (94.7%) 3796 (11.3) 10,178 (30.4) 19,529 (58.3) p < 0.01 A dispatcher 673 (1.9%) 104 (15.5) 202 (30.0) 367 (54.5) Service provider 1213 (3.4%) 345 (28.4) 340 (28.0) 528 (43.5) Company size (Number of workers in workplace) ≤ 49 38,891 (79.7%) 4976 (12.8) 11,531 (29.6) 22,384 (57.6) p < 0.01 50–299 6874 (14.1%) 670 (9.7) 2290 (33.3) 3914 (56.9) ≥ 300 3011 (6.2%) 254 (8.4) 995 (33.0) 1762 (58.5) Type of workplace Employer’s place of business 37,873 (76.7%) 3949 (10.4) 11,486 (30.3) 22,438 (59.2) p < 0.01 Customer’s place of business 4107 (8.3%) 694 (16.9) 1193 (29.0) 2220 (54.1) In the case of transportation such as cars 1388 (2.8%) 258 (18.6) 507 (36.5) 623 (44.9) Outdoor (construction site, field / etc.) 5304 (10.7%) 1039 (19.6) 1661 (31.3) 2604 (49.1) My house 533 (1.1%) 31 (5.8) 117 (22.0) 385 (72.2) Others 199 (0.4%) 16 (8.0) 52 (26.1) 131 (65.8) Job Category Manager 1354 (2.7%) 176 (13.0) 421 (31.1) 757 (55.9) p < 0.01 Specialist 3759 (7.6%) 149 (4.0) 930 (24.7) 2680 (71.3) Technician and Associate Expert 2505 (5.0%) 279 (11.1) 797 (31.8) 1429 (57.0) Office worker 10,545 (21.2%) 746 (7.1) 3061 (29.0) 6738 (63.9) Service worker 7666 (15.4%) 874 (11.4) 2140 (27.9) 4652 (60.7) Salesperson 7532 (15.2%) 695 (9.2) 2115 (28.1) 4722 (62.7) Experts in agriculture and forestry fishing 2951 (5.9%) 213 (7.2) 1014 (34.4) 1724 (58.4) Functional Person and Related Person 4492 (9.0%) 1101 (24.5) 1572 (35.0) 1819 (40.5) Machine Operator and Assembly Worker 3349 (6.7%) 733 (21.9) 1281 (38.3) 1335 (39.9) Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 4 of 9 Table 1 General characteristics of the study subjects (Continued) Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Laborer 5416 (10.9%) 1049 (19.4) 1719 (31.7) 2648 (48.9) Soldier 83 (0.2%) 4 (4.8) 46 (55.4) 33 (39.8) Occasionally need to wear personal protective equipment Yes 12,071 (24.4%) 2709 (22.4) 4116 (34.1) 5246 (43.5) p < 0.01 No 37,353 (75.6%) 3291 (8.8) 10,899 (29.2) 23,163 (62.0) Night working days in a month ≤ 9 2896 (46.0%) 518(17.9) 874 (30.2) 1504 (51.9) p < 0.01 10–19 2137 (34.0%) 392 (18.3) 763 (35.7) 982 (46.0) ≥ 20 1256 (20.0%) 361 (28.7) 343 (27.3) 552 (43.9) age group. The number of wage workers was 36,156 79.7% were employed at a workplace with less than 50 (72.8%) and number of respondents to the question employees. In the major categories of occupation, the about “wage worker type” and “wage provider” were office workers were the largest, followed by the service 35,913 and 35,389 respectively. Of the respondents, workers, the sales workers, and the simple laborers. 76.0% were permanent (regular) workers, 16.9% were From the chi-square test, the variables that showed temporary workers, and 7.1% were daily workers, re- significant differences in the exposure to SHS were gen- spectively. Of the respondents, 94.7% were provided der, age, occupation status, wage provider, the size of the wage from workplace. By the size of the workplace, workplace, type of workplace, job category, whether to Table 2 Multiple logistic analysis of factors affecting secondhand smoke exposure in workplace Dependent variables Adjusted OR (Odds Ratio) 95% CI (Confidence Interval) Sex (reference: Female) Male 4.107** 3.461 ~ 4.874 Age (reference: ≤39) 40–49 1.551** 1.348 ~ 1.785 50–59 1.529** 1.319 ~ 1.772 ≥ 60 1.116 0.916 ~ 1.360 Number of workers in workplace (reference: ≥ 300) ≤ 49 2.114** 1.721 ~ 2.595 50–300 1.545** 1.232 ~ 1.937 Status (reference: Permanent workers) Temporary workers 1.130 0.957 ~ 1.334 Daily workers 1.318** 1.102 ~ 1.575 Occasionally need to wear personal protective equipment (reference No) Yes 1.132 0.942 ~ 1.359 Wage_Provider (reference: Work place (last week’s work place)) A dispatcher 1.140 0.814 ~ 1.596 Service provider 1.736** 1.401 ~ 2.149 Type of Workplace (reference: Employer’s place of business Customer’s place of business 1.220* 1.014 ~ 1.466 In the case of transportation such as cars .696 0.466 ~ 1.040 Outdoor (construction site, field / etc.) 1.668** 1.423 ~ 1.956 My house 2.200 0.186 ~ 25.995 Adjusted by Sex, Age, Number of workers in workplace, Work status, need of personal protective equipment, Wage provider and Types of workplace * p < 0.05 ** p < 0.01 Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 5 of 9 wear the personal protective equipment, and the number types of occupation, the ESQ rate was highest in the func- of night shifts. The rate of exposure to SHS for more tional and related functional staff. The rate of SHS expos- than one quarter of working time (ESQ rate) was 16% ure was higher for workers wearing protective gear than for males and 6.9% for females. By age, the ESQ rate was for workers not wearing protective gear. A greater- num- highest in the 50s and by employment status, the ESQ ber of night shifts also increased SHS exposure (Table 1). rate was highest for self - employed with workers. Among the wage workers, the ESQ rate was highest for SHS exposure by job status the daily workers, and in terms of the wage-payment According to the logistic regression analysis (Table 2), method, the ESQ rate was highest for workers who were the risk of SHS exposure of males was 4.107 times (95% paid by service companies. In terms of the number of CI: 3.461 ~ 4.874) higher than that of females. By age employees at workplaces, the ESQ rate was highest for the groups, exposure for those in their forties was 1.551 companies with less than 50 employees and by types of times (95% CI: 1.348 ~ 1.785) and for those in their fif- workplace, the ESQ rate was highest in outdoor ties were 1.529 times (95% CI: 1.319 ~ 1.772) more than work-places, such as construction sites and farms. By for those under 39 years of age. In terms of the number Table 3 Secondhand smoke exposure affecting by discrimination experience Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Age discrimination Yes 2473 (5.0%) 438 (17.7) 739 (29.9) 1296 (52.4) p < 0.01 No 46,996 (95.0%) 5546 (11.8) 14,291 (30.4) 27,159 (57.8) Race discrimination Yes 442 (0.9%) 89 (20.1) 131 (29.6) 222 (50.2) p < 0.01 No 49,046 (99.1%) 5913 (12.1) 14,883 (30.3) 28,250 (57.6) Nationality discrimination Yes 417 (0.8%) 113 (27.1) 122 (29.3) 182 (43.6) p < 0.01 No 49,081 (99.2%) 5888 (12.0) 14,899 (30.4) 28,294 (57.6) Sex discrimination Yes 802 (1.6%) 132 (16.5) 240 (29.9) 430 (53.6) p < 0.01 No 48,698 (98.4%) 5859 (12.0) 14,803 (30.4) 28,036 (57.6) Religion discrimination Yes 143 (0.3%) 13 (9.1) 58 (40.6) 72 (50.3) p < 0.01 No 49,353 (99.7%) 5984 (12.1) 14,982 (30.4) 28,387 (57.5) Disability discrimination Yes 244 (0.5%) 68 (27.9) 77 (31.6) 99 (40.6) p < 0.01 No 49,197 (99.5%) 5924 (12.0) 14,930 (30.3) 28,343 (57.6) Sexual orientation discrimination Yes 188 (0.4%) 34 (18.1) 70 (37.2) 84 (44.7) p < 0.01 No 49,212 (99.6%) 5960 (12.1) 14,925 (30.3) 28,327 (57.6) Academic group discrimination Yes 2113 (4.3%) 299 (14.2) 596 (28.2) 1218 (57.6) p < 0.01 No 47,262 (95.7%) 5677 (12.0) 14,375 (30.4) 27,210 (57.6) Region of origin discrimination Yes 820 (1.7%) 154 (18.8) 261 (31.8) 405 (49.4) p < 0.01 No 48,610 (98.3%) 5831 (12.0) 14,743 (30.3) 28,036 (57.7) Employment status discrimination Yes 1593 (3.2%) 327 (20.5) 460 (28.9) 806 (50.6) p < 0.01 No 47,782 (96.8%) 5659 (11.8) 14,531 (30.4) 27,592 (57.7) Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 6 of 9 of workers in the workplace, the risk of exposure to SHS Discussion in companies with less than 50 workers was 2.114 times By job status (95% CI: 1.721 ~ 2.595) higher than that in companies In this study, we found that male workers in their 40s with more than 300 workers and that of daily workers and 50s, workers employed in workplaces with fewer was 1.318 times (95% CI: 1.102 ~ 1.575) higher than that than 50 employees, daily workers, temporary workers, of regular workers. The risk of exposure to SHS for and people working at the customer’s premises or workers receiving wages from the service provider was working outdoors had a higher risk of exposure to SHS 1.736 times higher than that for workers receiving wages than the others. The Dutch study reported that workers at work. The risk of exposure to SHS for outdoor who were male and low-educated were more likely to workers was 1.668 times higher than for those working be exposed to SHS [8]. The German study reported at the employer’s place of business. the aspect of higher SHS exposure in younger age group, but this is dependent on the place of exposure, and exceptionally at workplace, 30–44 years had high- est SHS exposure differ by the others such as home, SHS exposure by experience of discrimination at work bars, or the house of friend [9]. It is known that Examining the degree of exposure to SHS in terms of blue-collar workers and service workers are more likely experience of discrimination in the last 12 months in the to expose the higher rate of SHS occupationally than workplace, showed that workers who have experienced white-collar workers. These are serious concern because discrimination at work because of age (adjusted OR blue collar workers have exposed more often to chemical 1.637, 95% CI 1.468~1.825), race (adjusted OR 1.850, and dust and SHS related health problems can be synergis- 95% CI 1.459~2.347), nationality (adjusted OR 2.699, tically effect with those hazards [10]. 95% CI 2.161~3.371), sex (adjusted OR 1.969, 95% CI Also, we found workers who had experienced discrim- 1.623~2.389), disability (adjusted OR 2.758, 95% CI ination at workplace based on age, race, nationality, 2.069~3.676), sexual orientation (adjusted OR 1.801, gender, disability, academic group, place of origin, or 95% CI 1.231~2.633), academic group (adjusted OR 1.271, 95% CI 1.119~1.443), place of origin (adjusted OR Table 4 Multiple logistic analysis of factors affecting second 1.657, 95% CI 1.384~1.984), or employment status hand smoke exposure of discrimination experience (adjusted OR 2.010, 95% CI 1.770~2.283) were more Dependent OR(Odds Ratio, 95% CI) exposed to SHS than the counterparts who are not variables Crude OR Adjusted OR experienced discrimination (Tables 3 and 4). Age discrimination (reference No) Yes 1.607**(1.444~1.789) 1.637**(1.468~1.825) SHS exposure by occupations Race discrimination (reference No) Occupational groups (classification code: 2 digits) by Yes 1.848**(1.463~2.335) 1.850**(1.459~2.347) KSCO were analyzed and classified into 52 groups. Nationality discrimination (reference No) Construction and mining-related occupations (49.5%), Yes 2.719**(2.186~3.380) 2.699**(2.161~3.371) metal coremakers-related trade occupations (33.3%), and transport and machine-related trade occupations (31.4%) Sex discrimination (reference No) were the highest exposure groups for SHS at the workplace. Yes 1.444**(1.196~1.744) 1.969**(1.623~2.389) Public and enterprise senior, legal and administration Religion discrimination (reference No) professional occupations (0.9%), education professional and Yes 0.748(0.426~1.315) 0.837(0.473~1.480) related occupations (1.7%), and health, social welfare, and Disability discrimination (reference No) religion-related occupations (1.7%) were the lowest in Yes 2.820**(2.128~3.736) 2.758**(2.069~3.676) exposure to SHS at the workplace (Table 5). Specific jobs (classification code: 4 digits) by KSCO Sexual orientation discrimination (reference No) were analyzed and classified into 415 jobs. Of these, 151 Yes 1.594*(1.098~2.315) 1.801*(1.231~2.633) jobs with 50 or more respondents were analyzed. The Academic group discrimination (reference No) top 20 jobs for exposure to SHS for more than a quarter Yes 1.207*(1.065~1.368) 1.271**(1.119~1.443) of working time are shown in Table 6. Concrete- Region of origin discrimination (reference No) reinforcing iron workers (53.7%), plasters (52%), con- Yes 1.697**(1.421~2.027) 1.657**(1.384~1.984) struction and mining elementary workers (49.5%), con- struction plumbers (48.9%), and entertainment facilities Employment status discrimination (reference No) workers (47.9%) were the highest SHS exposure jobs. Yes 1.922**(1.697~2.178) 2.010**(1.770~2.283) Among the top 50 jobs, construction jobs accounted for Adjusted by age and sex about a dozen (Table 6). * p < 0.05 ** p < 0.01 Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 7 of 9 Table 5 Exposure to second hand smoke in workplace by occupation group (Top20) Occupation Group (Code) n The rate of exposure SHS in workplace over 1/4 working hours (Number (%)) Construction and Mining Related Elementary Occupations(91) 671 332 (49.5) Construction and Mining Related Trade Occupations(77) 1056 433 (41) Metal Coremakers Related Trade Occupations(74) 393 131 (33.3) Wood and Furniture, Musical Instrument and Signboard Related Trade 114 37 (32.5) Occupations(73) Transport and Machine Related Trade Occupations(75) 759 238 (31.4) Transport and Leisure Services Occupations(43) 328 101 (30.8) Wood, Printing and Other Machine Operating Occupations(89) 290 87 (30) Other Technical Occupations(79) 259 75 (29) Skilled Forestry Occupations(62) 12 3 (25) Skilled Fishery Occupations(63) 73 17 (23.3) Construction, Electricity and Production Related Managers(14) 181 41 (22.7) Driving and Transport Related Occupations(87) 2503 539 (21.5) Metal and Nonmetal Related Operator Occupations(84) 233 47 (20.2) Machine Production and Related Machine Operators(85) 1069 214 (20) Electric and Electronic Related Trade Occupations(76) 458 89 (19.4) Chemical Related Machine Operating Occupations(83) 283 54 (19.1) Video and Telecommunications Equipment Related Occupations(78) 108 20 (18.5) Police, Fire Fight and Security Related Service Occupations(41) 401 70 (17.5) Transport Related Elementary Occupations(92) 713 118 (16.5) Clean and Guard Related Elementary Occupations(94) 2120 341 (16.1) Korean Standard Classification of Occupation code (2 digit code) type of employment were more likely to experience a exposed occupations were public and enterprise senior higher rate of exposure to tobacco smoke than were officers, legal and administrative professions, education their counterparts who had not experienced discrimin- professionals, and health, social welfare, and religion- ation. A recent study reported that exposure to discrim- related occupations. Wortley et al. (2002) [8] compared ination based on age, academic group or employment the levels of serum cotinine in nonsmokers to assess the status put the workers at a high risk of having a poor risk of SHS exposure based on NHANES III (1988– well-being [12]. Another study also reported an associ- 1994) and found that among 40 occupational groups, ation between SHS and psychological well-being and the geometric mean of serum cotinine was highest in emphasized the importance of reducing SHS exposure at the waiter and waitress group (0.47 ng/mL), among the workplace [13]. From these studies, exposure to dis- seven job categories, the geometric mean of serum crimination and SHS are both significantly more likely cotinine was highest in the device operation, producer, to induce a poor well-being than counterparts who were and laborer (0.22 ng/mL). The research data related SHS not exposed to discrimination and SHS. exposure by occupation were rare to find, instead we can refer to the smoking rate by occupations. Based on By occupations the NHANES(National Health and Nutrition Examin- The top ten occupations with the highest SHS exposure ation Survey) III in the United States, 1988–1994, smok- were construction and mining-related occupations, ing rates by occupation showed that material-moving construction and mining-related trade occupations, occupations, construction laborers, and vehicle mechan- metal coremakers-related trade occupations, wood and ics and repairers had the highest smoking rate, whereas furniture, musical instrument, and signboard-related teachers and sales representatives reported that the rate trade occupations, transport and machine-related trade of smoking was low [14]. Smith and Leggat (2007) [15] occupations, transport and leisure services occupations, reported that by job category, smoking was most wood, printing and other machine-operating occupa- common among laborers and least common among tions, other technical occupations, and skilled forestry professionals, managers, or administrators. Occupations occupations, skilled fishery occupations. The least with high smoking rates were very similar to Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 8 of 9 Table 6 Exposure to second hand smoke in workplace by specified jobs (Top 20) Specified job (Code) n The rate of exposure SHS in workplace over 1/4 working hours (Number (%)) Concrete Reinforcing Iron Workers(7721) 67 36 (53.7) Plasters(7731) 102 53 (52) Construction and Mining Elementary Workers(910) 671 332 (49.5) Construction Plumbers(7921) 88 43 (48.9) Entertainment Facilities Workers(4323) 192 92 (47.9) Construction Painters(7736) 94 41 (43.6) Floor Installers(7734) 61 26 (42.6) Automobile Mechanics(751) 418 170 (40.7) Window Chassis Assembers and Installers(7737) 87 35 (40.2) Construction Carpenters(7724) 269 102 (37.9) Furniture Makers and Repairers(7302) 66 25 (37.9) Other Construction Finishing Related Technical Workers(7739) 99 37 (37.4) Printing Machine Operators(8921) 170 63 (37.1) Street Stall Salespersons and Vendors(5305) 79 29 (36.7) Welders(743) 335 122 (36.4) Cutters(7212) 68 23 (33.8) Interior Electricians(7622) 172 56 (32.6) Construction and Mining Related Managers(1411) 109 33 (30.3) Machine Tool Operators(851) 344 100 (29.1) Handling Equipment Operators(874) 239 69 (28.9) Korean Standard Classification of Occupation code (4 digit code) occupations with high SHS rates in our study. Tobacco effective way to reduce the SHS rate in the workplace smoke represents an occupational hazard and a and can be more effective if specifically designed for the smoke-free environment is an essential component of a various occupations and working styles in each country. healthy and safe. Smith and Leggat [15] reported that Particularly in South Korea, workers in their 40s and smoking rates were higher among unemployed persons 50s, workers employed in workplaces with less than 50 in many European countries like France, Italy, and employees, daily workers and temporary workers, Sweden, the United States and Australia, whereas in workers who work outside, and construction workers Japan, people who were currently employed actually had are priority target for non-smoking regulations at work. the higher smoking rates. These results can be affected Acknowledgements by different working condition including job status and The paper’s contents are solely the responsibility of the author and do not occupation of each country. Therefore it is necessary to necessarily represent the official vies of the OSHRI. analyze the smoking and SHS exposure rates in job status and occupation for each country. Funding Not applicable. The strength of this study is to analyze the SHS expos- ure by job status and occupations and identify the prior- Availability of data and materials ity group to implement smoking ban policy and confirm The present study used data from the 4th Korean Working Conditions Survey the workplace smoking is an occupational health hazard (KWCS), which was conducted between June and September 2014 on and a smoking ban policy at the workplace is the best employed workers, 15 years or older by the Occupational Safety and Health Research Institute (OSHRI) affiliated under the Ministry of Employment and option to reduce SHS. But, the limitation of study is that Labor. This data is open for anyone to use. in 4th KWCS data, participant’s smoking status was not surveyed and we have not been able to identify how Authors’ contributions much SHS exposure is affected by whether or not partic- HP analyzed research data, interpretated the result and written this paper, SC made conception and design of this paper and CL double-analyzed and ipants are smokers. re-checked the data analysis. All authors read and approved the final manuscript. Conclusions Tobacco smoke is a significant occupational hazard. Ethics approval and consent to participate Smoking cessation ban in the workplace can be a very Not applicable. Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 9 of 9 Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 20 June 2018 Accepted: 17 January 2019 References 1. Jain RB. Exposure to second hand smoke at home and work among nonsmokers. Chemosphere. 2015;135:225–32. 2. National Health Statistics for 2015 (National Health Effects Survey, Phase 6, Third Year Data), Disease Control Headquarters. https://knhanes.cdc.go.kr/ knhanes/sub01/sub01_05.jsp#s5_01_01. Accessed 15 Aug 2018 3. OECD Data; Health at a glance (2017). https://data.oecd.org/healthrisk/daily- smokers.htm. Accessed 15 Aug 2018. 4. National Health Promotion Act, Article 9 (Date 31, Dec, 2011). https://elaw. klri.re.kr/eng_service/lawView.do?hseq=43278&lang=ENG. 5. Pickett MS, Schober ES, Brody DJ, Curtin LR, Giovino GA. Smoke-free laws and secondhand smoke exposure in US non-smoking adults, 1999–200. Tobacco Control. 2006;15(4):302–7. 6. State Smoking CDC. Restrictions for private-sector worksites, restaurants, and bars. Oncol Times. 2006;28(1):32–4. 7. Arheart KL, Lee DJ, Dietz NA, Wilkinson JD, Clark JD. Declining trends in serum cotinine levels in US worker groups: the power of policy. J Occup Environ Med. 2008;50(1):57–63. 8. Wortley PM, Caraballo RS, Pederson LL, Pechacek TF. Exposure to secondhand smoke in the workplace: serum cotinine by occupation. J Occup Environ Med. 2002;44(6):503–9. 9. Fischer F, Kraemer A. Factors associated with secondhand smoke exposure in different setting: results from the German health update(GEDA) 2012. BMC Public Health. 2016;16:327–36. 10. Howard J. Smoking is an occupational hazards. Am J Ind Med. 2004;46(2):161–9. 11. Verdonk-Kleinjan WM, Knibbe RA, Tan FE, Willemsen MC, de Groot HN, de Vries H. Does the workplace-smoking ban eliminate differences in risk for environmental tobacco smoke exposure at work? Health Policy. 2009;92(2–3):197–202. 12. Lee HS, Kim GH, Jung SW, Lee JH, Lee KJ, Kim JJ. The association between perceived discriminations and well-being in Korean employed workers: the 4th Korean working conditions survey. Ann Occup Environ Med. 2017;29:46. 13. Kim SJ, Lamichhane DK, Park SG, Lee BJ, Moon SH, Park SM, Jang HS, Kim HC. Association between second-hand smoke and psychological well-being amongst non-smoking wageworkers in Republic of Korea. Ann Occup Environ Med. 2016;28:49. 14. Bang KM, Kim JH. Prevalence of cigarette smoking by occupation and industry in the United States. American J Industrial Medicine. 2001;40:233–9. 15. Smith DR, Leggat PA. Tobacco Smoking by occupation in Australia; results from the 2004 to 2005 National Health Survey. J Occup Environ Med. 2007;49:437–45. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Occupational and Environmental Medicine Springer Journals

Second hand smoke exposure in workplace by job status and occupations

Download PDF
9 pages

Loading next page...
 
/lp/springer-journals/second-hand-smoke-exposure-in-workplace-by-job-status-and-occupations-GRN7pkGqYO
Publisher
Springer Journals
Copyright
Copyright © 2019 by The Author(s).
Subject
Medicine & Public Health; Public Health; Occupational Medicine/Industrial Medicine
eISSN
2052-4374
DOI
10.1186/s40557-019-0282-z
Publisher site
See Article on Publisher Site

Abstract

Background: The objective of this study is to evaluate the risk of exposure to second hand smoke (SHS) during working hours by job status and occupation. Methods: Using the 4th Korean Working Conditions Survey (KWCS), 49,674 respondents who answered the question about SHS were studied. A chi-square test was carried out to determine whether there is a significant different in SHS exposure frequency by general and occupational characteristics and experience of discrimination at work and logistic regression analysis was carried out to identify the risk level of SHS exposure by variables. Results: In this study, we found that male workers in their 40s and 50s, workers employed in workplaces with fewer than 50 employees, daily workers, and people working outdoors had a higher rate of exposure to SHS than the others. The top five occupations with the highest SHS exposure were construction and mining-related occupations, metal core-makers-related trade occupations, wood and furniture, musical instrument, and signboard- related trade occupations, transport and machine-related trade occupations, transport and leisure services occupations. The least five exposed occupations were public and enterprise senior officers, legal and administrative professions, education professionals, and health, social welfare, and religion-related occupations. Conclusion: Tobacco smoke is a significant occupational hazard. Smoking ban policy in the workplace can be a very effective way to reduce the SHS exposure rate in the workplace and can be more effective if specifically designed by the job status and various occupations. Keywords: Second hand smoke exposure, Job status, Occupations, Smoking ban Background smoking rate for Korean males aged more than 15 was Second hand smoke (SHS), which is exposure to smoke 31.4% as of 2015, which was the third highest rank among from cigarette butts or smoke exhaled by smokers, is OECD countries. The Korean government has imple- itself a Group 1 carcinogen for the human as classified mented a policy of smoking bans in public places for by the International Agency for Research on Cancer many years, but that smoking policy only applies with a (IARC). Exposure to SHS is known to be associated with workplace more than 1000 m in total area [4]. For that respiratory and cardiovascular diseases as well as anxiety reason, the workplace is still at a high rate of SHS expos- disorders, mental health, and psychological stress [1]. ure and could be the environment that can be improved According to the National Health Statistics in Korea for further in SHS exposure reduction. 2015 [2], the current indoor SHS exposure rate of non- From 1999 to 2002 US NHANES (National Health smokers at work was 26.8%, remarkably high compared and Nutrition Examination Survey) data, there have with at home, which is 8.2%. From OECD (Organization been dramatic reduction in the serum cotinine levels for Economic Cooperation and Development) data [3], the caused by successful smoking-free laws [5]. Although SHS exposure rates are declining, the workplace remains a significant source of SHS exposure [6, 7]. Working * Correspondence: bioaerosol@kosha.or.kr Work Environment Research Bureau, Occupational Safety and Health adults spend most of their time at workplace and for Research Institute, 400, Jongga-ro, Jung-gu, Ulsan, Republic of Korea those non-smokers, the workplace may be the major Department of Public Health Science, Graduate School of Public Health, and source of provider to SHS exposure [8]. In the German Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 2 of 9 study, More than 40% of non-smokers reported experi- (ESQ rate) was used to compare the SHS exposure by encing SHS at work [9]. Workplace smoking is an occupa- independent variables. tional health hazard and a smoking ban policy at the Independent variables included information on gender workplace is the best option to reduce SHS [10]. More (“male” and “female”), age group ( “≤ 39”, “40–49”, “50–59” than 50% of European countries enforce non-smoking and “≥ 60”), job status (“self-employed without workers”, regulations at work and the other European countries also “self-employed with workers”, “wage workers (employees)”, partially restrict smoking at work. In the Netherlands, the “unpaid family worker” and “other workers”), type of wage comparison of SHS exposure rates before and after the worker (“permanent workers”, “temporary workers” and implementation of the smoking ban policy in the work- “daily workers”), wage provider (“workplace”, “adispatcher” place showed that the SHS exposure rate decreased from and “service provider”), Companysizeas numberof 70.7 to 51.9%. However, the rate of SHS exposure is still workers in workplace ( “≤ 49”, “50–299” and “≥ 300”), type high in the Netherlands even after the smoking ban at of workplace (“employer’s place of business”, “customer’s work, because of a high-risk group for smoking such as place of business”, “in the case of transportation as cars”, males and low-educated workers [11]. “outdoor (construction, field/etc)”, “my home” and To reinforce the appropriated non-smoking policy at “others”), job category (“manager”, “specialist”, “technician workplace, it is important to identify priority group to and associate export”, “office worker”, “service worker”, implement such as vulnerable job status and occupations “sales worker”, “experts in agriculture and forestry fishing”, to SHS exposure. In this study, we evaluated the risk of “functional person and related person”, “machine operator exposure to tobacco smoke by others during working and assembly worker”, “laborer” and “soldier”), and night hours by job status, experience of discrimination at work working days in a month ( “≤ 9”, “10–19” and “≥ 20”). and occupation using the data of the 4th Korean Work- The item designed to evaluate the experience of dis- ing Conditions Survey (KWCS). crimination at the workplace was used as a variables for the effect of exposure to SHS. The question is “During the past 12 months, did you experience to discrimin- Methods ation at your workplace related to age, race, nationality, Study subjects gender, religion, disability, sexual orientation, academic This study used data from the 4th Korean Working Con- group, region of origin, or employment status?” Respon- ditions Survey (KWCS), which was conducted between dents answered to the question about discrimination June and September 2014 on employed workers by the with ‘yes’ or ‘no’. Occupational Safety and Health Research Institute The occupational categories of respondents were clas- (OSHRI) affiliated under the Ministry of Employment and sified according to the Korean Standard Classification of Labor. The KWCS selected individuals who satisfied cri- Occupation (KSCO by National Statistical Office) and teria for the definition of “economically active population” classified into occupational groups (52 groups, classifica- conducted one-on-one interviews at their home by a pro- tion code: 2 digits) and detailed occupation (415 groups, fessional interviewer. The total sample of 50,007 persons, classification code: 4 digits). 15 years or older participated in this survey. The data used in this study are from 49,674 respondents who answered Statistical analysis the question “Are you exposed at work to tobacco smoke Data were analyzed using PASW version 18.0 (SPSS Inc., from other people?” Chicago, IL, USA). Weight is applied when conducting statistical analysis based on the results of the “economic- Variables selected for analysis ally active population survey (EAPS)” in 2014 conducted The dependent variable was assessed to evaluate the risk by National Statistical Office. A chi-square test was of exposure to SHS by a question, “Are you exposed at carried out to determine whether there is a significant work to tobacco smoke from other people?” Respon- different between SHS exposure frequency by general dents answered on a seven-point scale of SHS exposure and occupational characteristics and experience of frequency; the choices were (in terms of all of the work- discrimination at work and logistic regression analysis ing time), “all”, “almost”, “3/4”, “half”, “1/4”, “almost was carried out to identify the risk level of SHS exposure never”, and “never”. For chi-square test, exposure to by variables. SHS in workplace was categorized into 3 group; “over 1/ 4 workhours” (all ~ 1/4), “almost never” and “never”. For Results logistic regression exposure to SHS in workplace was General characteristics of population categorized into 2 group; “over 1/4 workhours” (all ~ 1/ The sample characteristics are described in Table 1.Of 4) or “less than 1/4” (almost never and never). The rate the total 49,674 respondents, 57.8% were male and of exposure to SHS for more than 1/4 of workhours 36.9% were under the age of 39 which was the largest Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 3 of 9 Table 1 General characteristics of the study subjects Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Gender Male 28,732 (57.8%) 4587 (16.0) 9163 (31.9) 14,982 (52.1) p < 0.01 Female 20,942 (42.2%) 1441 (6.9) 5939 (28.4) 13,562 (64.8) Age(yrs) ≤ 39 18,351 (36.9%) 1661 (9.1) 5341 (29.1) 11,349 (61.8) p < 0.01 40–49 12,958 (26.1%) 1777 (13.7) 3929 (30.3) 7252 (56.0) 50–59 11,348 (22.8%) 1698 (15.0) 3608 (31.8) 6042 (53.2) ≥ 60 7017 (14.1%) 892 (12.7) 2224 (31.7) 3901 (55.6) Job status Self-employed without workers 8058 (16.2%) 915 (11.4) 2449 (30.4) 4694 (58.3) p < 0.01 Self-employed with workers 3012 (6.1%) 522 (17.3) 913 (30.3) 1577 (52.4) Wage workers (employees) 36,156 (72.8%) 4344 (12.0) 10,956 (30.3) 20,856 (57.7) Unpaid family worker 2417 (4.9%) 244 (10.1) 767 (31.7) 1406 (58.2) Other workers 27 (0.1%) 3 (11.1) 14 (51.9) 10 (37.0) Type of wage workers Permanent workers 27,279 (76.0%) 2900 (10.6) 8459 (31.0) 15,920 (58.4) p < 0.01 Temporary workers 6083 (16.9%) 722 (11.9) 1709 (28.1) 3652 (60.0) Daily workers 2551 (7.1%) 675 (26.5) 716 (28.1) 1160 (45.5) Wage_provider Work place 33,503 (94.7%) 3796 (11.3) 10,178 (30.4) 19,529 (58.3) p < 0.01 A dispatcher 673 (1.9%) 104 (15.5) 202 (30.0) 367 (54.5) Service provider 1213 (3.4%) 345 (28.4) 340 (28.0) 528 (43.5) Company size (Number of workers in workplace) ≤ 49 38,891 (79.7%) 4976 (12.8) 11,531 (29.6) 22,384 (57.6) p < 0.01 50–299 6874 (14.1%) 670 (9.7) 2290 (33.3) 3914 (56.9) ≥ 300 3011 (6.2%) 254 (8.4) 995 (33.0) 1762 (58.5) Type of workplace Employer’s place of business 37,873 (76.7%) 3949 (10.4) 11,486 (30.3) 22,438 (59.2) p < 0.01 Customer’s place of business 4107 (8.3%) 694 (16.9) 1193 (29.0) 2220 (54.1) In the case of transportation such as cars 1388 (2.8%) 258 (18.6) 507 (36.5) 623 (44.9) Outdoor (construction site, field / etc.) 5304 (10.7%) 1039 (19.6) 1661 (31.3) 2604 (49.1) My house 533 (1.1%) 31 (5.8) 117 (22.0) 385 (72.2) Others 199 (0.4%) 16 (8.0) 52 (26.1) 131 (65.8) Job Category Manager 1354 (2.7%) 176 (13.0) 421 (31.1) 757 (55.9) p < 0.01 Specialist 3759 (7.6%) 149 (4.0) 930 (24.7) 2680 (71.3) Technician and Associate Expert 2505 (5.0%) 279 (11.1) 797 (31.8) 1429 (57.0) Office worker 10,545 (21.2%) 746 (7.1) 3061 (29.0) 6738 (63.9) Service worker 7666 (15.4%) 874 (11.4) 2140 (27.9) 4652 (60.7) Salesperson 7532 (15.2%) 695 (9.2) 2115 (28.1) 4722 (62.7) Experts in agriculture and forestry fishing 2951 (5.9%) 213 (7.2) 1014 (34.4) 1724 (58.4) Functional Person and Related Person 4492 (9.0%) 1101 (24.5) 1572 (35.0) 1819 (40.5) Machine Operator and Assembly Worker 3349 (6.7%) 733 (21.9) 1281 (38.3) 1335 (39.9) Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 4 of 9 Table 1 General characteristics of the study subjects (Continued) Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Laborer 5416 (10.9%) 1049 (19.4) 1719 (31.7) 2648 (48.9) Soldier 83 (0.2%) 4 (4.8) 46 (55.4) 33 (39.8) Occasionally need to wear personal protective equipment Yes 12,071 (24.4%) 2709 (22.4) 4116 (34.1) 5246 (43.5) p < 0.01 No 37,353 (75.6%) 3291 (8.8) 10,899 (29.2) 23,163 (62.0) Night working days in a month ≤ 9 2896 (46.0%) 518(17.9) 874 (30.2) 1504 (51.9) p < 0.01 10–19 2137 (34.0%) 392 (18.3) 763 (35.7) 982 (46.0) ≥ 20 1256 (20.0%) 361 (28.7) 343 (27.3) 552 (43.9) age group. The number of wage workers was 36,156 79.7% were employed at a workplace with less than 50 (72.8%) and number of respondents to the question employees. In the major categories of occupation, the about “wage worker type” and “wage provider” were office workers were the largest, followed by the service 35,913 and 35,389 respectively. Of the respondents, workers, the sales workers, and the simple laborers. 76.0% were permanent (regular) workers, 16.9% were From the chi-square test, the variables that showed temporary workers, and 7.1% were daily workers, re- significant differences in the exposure to SHS were gen- spectively. Of the respondents, 94.7% were provided der, age, occupation status, wage provider, the size of the wage from workplace. By the size of the workplace, workplace, type of workplace, job category, whether to Table 2 Multiple logistic analysis of factors affecting secondhand smoke exposure in workplace Dependent variables Adjusted OR (Odds Ratio) 95% CI (Confidence Interval) Sex (reference: Female) Male 4.107** 3.461 ~ 4.874 Age (reference: ≤39) 40–49 1.551** 1.348 ~ 1.785 50–59 1.529** 1.319 ~ 1.772 ≥ 60 1.116 0.916 ~ 1.360 Number of workers in workplace (reference: ≥ 300) ≤ 49 2.114** 1.721 ~ 2.595 50–300 1.545** 1.232 ~ 1.937 Status (reference: Permanent workers) Temporary workers 1.130 0.957 ~ 1.334 Daily workers 1.318** 1.102 ~ 1.575 Occasionally need to wear personal protective equipment (reference No) Yes 1.132 0.942 ~ 1.359 Wage_Provider (reference: Work place (last week’s work place)) A dispatcher 1.140 0.814 ~ 1.596 Service provider 1.736** 1.401 ~ 2.149 Type of Workplace (reference: Employer’s place of business Customer’s place of business 1.220* 1.014 ~ 1.466 In the case of transportation such as cars .696 0.466 ~ 1.040 Outdoor (construction site, field / etc.) 1.668** 1.423 ~ 1.956 My house 2.200 0.186 ~ 25.995 Adjusted by Sex, Age, Number of workers in workplace, Work status, need of personal protective equipment, Wage provider and Types of workplace * p < 0.05 ** p < 0.01 Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 5 of 9 wear the personal protective equipment, and the number types of occupation, the ESQ rate was highest in the func- of night shifts. The rate of exposure to SHS for more tional and related functional staff. The rate of SHS expos- than one quarter of working time (ESQ rate) was 16% ure was higher for workers wearing protective gear than for males and 6.9% for females. By age, the ESQ rate was for workers not wearing protective gear. A greater- num- highest in the 50s and by employment status, the ESQ ber of night shifts also increased SHS exposure (Table 1). rate was highest for self - employed with workers. Among the wage workers, the ESQ rate was highest for SHS exposure by job status the daily workers, and in terms of the wage-payment According to the logistic regression analysis (Table 2), method, the ESQ rate was highest for workers who were the risk of SHS exposure of males was 4.107 times (95% paid by service companies. In terms of the number of CI: 3.461 ~ 4.874) higher than that of females. By age employees at workplaces, the ESQ rate was highest for the groups, exposure for those in their forties was 1.551 companies with less than 50 employees and by types of times (95% CI: 1.348 ~ 1.785) and for those in their fif- workplace, the ESQ rate was highest in outdoor ties were 1.529 times (95% CI: 1.319 ~ 1.772) more than work-places, such as construction sites and farms. By for those under 39 years of age. In terms of the number Table 3 Secondhand smoke exposure affecting by discrimination experience Variables n Exposure to SHS in Workplace (Number (%)) p-value Over 1/4 workhours Almost never Never Age discrimination Yes 2473 (5.0%) 438 (17.7) 739 (29.9) 1296 (52.4) p < 0.01 No 46,996 (95.0%) 5546 (11.8) 14,291 (30.4) 27,159 (57.8) Race discrimination Yes 442 (0.9%) 89 (20.1) 131 (29.6) 222 (50.2) p < 0.01 No 49,046 (99.1%) 5913 (12.1) 14,883 (30.3) 28,250 (57.6) Nationality discrimination Yes 417 (0.8%) 113 (27.1) 122 (29.3) 182 (43.6) p < 0.01 No 49,081 (99.2%) 5888 (12.0) 14,899 (30.4) 28,294 (57.6) Sex discrimination Yes 802 (1.6%) 132 (16.5) 240 (29.9) 430 (53.6) p < 0.01 No 48,698 (98.4%) 5859 (12.0) 14,803 (30.4) 28,036 (57.6) Religion discrimination Yes 143 (0.3%) 13 (9.1) 58 (40.6) 72 (50.3) p < 0.01 No 49,353 (99.7%) 5984 (12.1) 14,982 (30.4) 28,387 (57.5) Disability discrimination Yes 244 (0.5%) 68 (27.9) 77 (31.6) 99 (40.6) p < 0.01 No 49,197 (99.5%) 5924 (12.0) 14,930 (30.3) 28,343 (57.6) Sexual orientation discrimination Yes 188 (0.4%) 34 (18.1) 70 (37.2) 84 (44.7) p < 0.01 No 49,212 (99.6%) 5960 (12.1) 14,925 (30.3) 28,327 (57.6) Academic group discrimination Yes 2113 (4.3%) 299 (14.2) 596 (28.2) 1218 (57.6) p < 0.01 No 47,262 (95.7%) 5677 (12.0) 14,375 (30.4) 27,210 (57.6) Region of origin discrimination Yes 820 (1.7%) 154 (18.8) 261 (31.8) 405 (49.4) p < 0.01 No 48,610 (98.3%) 5831 (12.0) 14,743 (30.3) 28,036 (57.7) Employment status discrimination Yes 1593 (3.2%) 327 (20.5) 460 (28.9) 806 (50.6) p < 0.01 No 47,782 (96.8%) 5659 (11.8) 14,531 (30.4) 27,592 (57.7) Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 6 of 9 of workers in the workplace, the risk of exposure to SHS Discussion in companies with less than 50 workers was 2.114 times By job status (95% CI: 1.721 ~ 2.595) higher than that in companies In this study, we found that male workers in their 40s with more than 300 workers and that of daily workers and 50s, workers employed in workplaces with fewer was 1.318 times (95% CI: 1.102 ~ 1.575) higher than that than 50 employees, daily workers, temporary workers, of regular workers. The risk of exposure to SHS for and people working at the customer’s premises or workers receiving wages from the service provider was working outdoors had a higher risk of exposure to SHS 1.736 times higher than that for workers receiving wages than the others. The Dutch study reported that workers at work. The risk of exposure to SHS for outdoor who were male and low-educated were more likely to workers was 1.668 times higher than for those working be exposed to SHS [8]. The German study reported at the employer’s place of business. the aspect of higher SHS exposure in younger age group, but this is dependent on the place of exposure, and exceptionally at workplace, 30–44 years had high- est SHS exposure differ by the others such as home, SHS exposure by experience of discrimination at work bars, or the house of friend [9]. It is known that Examining the degree of exposure to SHS in terms of blue-collar workers and service workers are more likely experience of discrimination in the last 12 months in the to expose the higher rate of SHS occupationally than workplace, showed that workers who have experienced white-collar workers. These are serious concern because discrimination at work because of age (adjusted OR blue collar workers have exposed more often to chemical 1.637, 95% CI 1.468~1.825), race (adjusted OR 1.850, and dust and SHS related health problems can be synergis- 95% CI 1.459~2.347), nationality (adjusted OR 2.699, tically effect with those hazards [10]. 95% CI 2.161~3.371), sex (adjusted OR 1.969, 95% CI Also, we found workers who had experienced discrim- 1.623~2.389), disability (adjusted OR 2.758, 95% CI ination at workplace based on age, race, nationality, 2.069~3.676), sexual orientation (adjusted OR 1.801, gender, disability, academic group, place of origin, or 95% CI 1.231~2.633), academic group (adjusted OR 1.271, 95% CI 1.119~1.443), place of origin (adjusted OR Table 4 Multiple logistic analysis of factors affecting second 1.657, 95% CI 1.384~1.984), or employment status hand smoke exposure of discrimination experience (adjusted OR 2.010, 95% CI 1.770~2.283) were more Dependent OR(Odds Ratio, 95% CI) exposed to SHS than the counterparts who are not variables Crude OR Adjusted OR experienced discrimination (Tables 3 and 4). Age discrimination (reference No) Yes 1.607**(1.444~1.789) 1.637**(1.468~1.825) SHS exposure by occupations Race discrimination (reference No) Occupational groups (classification code: 2 digits) by Yes 1.848**(1.463~2.335) 1.850**(1.459~2.347) KSCO were analyzed and classified into 52 groups. Nationality discrimination (reference No) Construction and mining-related occupations (49.5%), Yes 2.719**(2.186~3.380) 2.699**(2.161~3.371) metal coremakers-related trade occupations (33.3%), and transport and machine-related trade occupations (31.4%) Sex discrimination (reference No) were the highest exposure groups for SHS at the workplace. Yes 1.444**(1.196~1.744) 1.969**(1.623~2.389) Public and enterprise senior, legal and administration Religion discrimination (reference No) professional occupations (0.9%), education professional and Yes 0.748(0.426~1.315) 0.837(0.473~1.480) related occupations (1.7%), and health, social welfare, and Disability discrimination (reference No) religion-related occupations (1.7%) were the lowest in Yes 2.820**(2.128~3.736) 2.758**(2.069~3.676) exposure to SHS at the workplace (Table 5). Specific jobs (classification code: 4 digits) by KSCO Sexual orientation discrimination (reference No) were analyzed and classified into 415 jobs. Of these, 151 Yes 1.594*(1.098~2.315) 1.801*(1.231~2.633) jobs with 50 or more respondents were analyzed. The Academic group discrimination (reference No) top 20 jobs for exposure to SHS for more than a quarter Yes 1.207*(1.065~1.368) 1.271**(1.119~1.443) of working time are shown in Table 6. Concrete- Region of origin discrimination (reference No) reinforcing iron workers (53.7%), plasters (52%), con- Yes 1.697**(1.421~2.027) 1.657**(1.384~1.984) struction and mining elementary workers (49.5%), con- struction plumbers (48.9%), and entertainment facilities Employment status discrimination (reference No) workers (47.9%) were the highest SHS exposure jobs. Yes 1.922**(1.697~2.178) 2.010**(1.770~2.283) Among the top 50 jobs, construction jobs accounted for Adjusted by age and sex about a dozen (Table 6). * p < 0.05 ** p < 0.01 Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 7 of 9 Table 5 Exposure to second hand smoke in workplace by occupation group (Top20) Occupation Group (Code) n The rate of exposure SHS in workplace over 1/4 working hours (Number (%)) Construction and Mining Related Elementary Occupations(91) 671 332 (49.5) Construction and Mining Related Trade Occupations(77) 1056 433 (41) Metal Coremakers Related Trade Occupations(74) 393 131 (33.3) Wood and Furniture, Musical Instrument and Signboard Related Trade 114 37 (32.5) Occupations(73) Transport and Machine Related Trade Occupations(75) 759 238 (31.4) Transport and Leisure Services Occupations(43) 328 101 (30.8) Wood, Printing and Other Machine Operating Occupations(89) 290 87 (30) Other Technical Occupations(79) 259 75 (29) Skilled Forestry Occupations(62) 12 3 (25) Skilled Fishery Occupations(63) 73 17 (23.3) Construction, Electricity and Production Related Managers(14) 181 41 (22.7) Driving and Transport Related Occupations(87) 2503 539 (21.5) Metal and Nonmetal Related Operator Occupations(84) 233 47 (20.2) Machine Production and Related Machine Operators(85) 1069 214 (20) Electric and Electronic Related Trade Occupations(76) 458 89 (19.4) Chemical Related Machine Operating Occupations(83) 283 54 (19.1) Video and Telecommunications Equipment Related Occupations(78) 108 20 (18.5) Police, Fire Fight and Security Related Service Occupations(41) 401 70 (17.5) Transport Related Elementary Occupations(92) 713 118 (16.5) Clean and Guard Related Elementary Occupations(94) 2120 341 (16.1) Korean Standard Classification of Occupation code (2 digit code) type of employment were more likely to experience a exposed occupations were public and enterprise senior higher rate of exposure to tobacco smoke than were officers, legal and administrative professions, education their counterparts who had not experienced discrimin- professionals, and health, social welfare, and religion- ation. A recent study reported that exposure to discrim- related occupations. Wortley et al. (2002) [8] compared ination based on age, academic group or employment the levels of serum cotinine in nonsmokers to assess the status put the workers at a high risk of having a poor risk of SHS exposure based on NHANES III (1988– well-being [12]. Another study also reported an associ- 1994) and found that among 40 occupational groups, ation between SHS and psychological well-being and the geometric mean of serum cotinine was highest in emphasized the importance of reducing SHS exposure at the waiter and waitress group (0.47 ng/mL), among the workplace [13]. From these studies, exposure to dis- seven job categories, the geometric mean of serum crimination and SHS are both significantly more likely cotinine was highest in the device operation, producer, to induce a poor well-being than counterparts who were and laborer (0.22 ng/mL). The research data related SHS not exposed to discrimination and SHS. exposure by occupation were rare to find, instead we can refer to the smoking rate by occupations. Based on By occupations the NHANES(National Health and Nutrition Examin- The top ten occupations with the highest SHS exposure ation Survey) III in the United States, 1988–1994, smok- were construction and mining-related occupations, ing rates by occupation showed that material-moving construction and mining-related trade occupations, occupations, construction laborers, and vehicle mechan- metal coremakers-related trade occupations, wood and ics and repairers had the highest smoking rate, whereas furniture, musical instrument, and signboard-related teachers and sales representatives reported that the rate trade occupations, transport and machine-related trade of smoking was low [14]. Smith and Leggat (2007) [15] occupations, transport and leisure services occupations, reported that by job category, smoking was most wood, printing and other machine-operating occupa- common among laborers and least common among tions, other technical occupations, and skilled forestry professionals, managers, or administrators. Occupations occupations, skilled fishery occupations. The least with high smoking rates were very similar to Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 8 of 9 Table 6 Exposure to second hand smoke in workplace by specified jobs (Top 20) Specified job (Code) n The rate of exposure SHS in workplace over 1/4 working hours (Number (%)) Concrete Reinforcing Iron Workers(7721) 67 36 (53.7) Plasters(7731) 102 53 (52) Construction and Mining Elementary Workers(910) 671 332 (49.5) Construction Plumbers(7921) 88 43 (48.9) Entertainment Facilities Workers(4323) 192 92 (47.9) Construction Painters(7736) 94 41 (43.6) Floor Installers(7734) 61 26 (42.6) Automobile Mechanics(751) 418 170 (40.7) Window Chassis Assembers and Installers(7737) 87 35 (40.2) Construction Carpenters(7724) 269 102 (37.9) Furniture Makers and Repairers(7302) 66 25 (37.9) Other Construction Finishing Related Technical Workers(7739) 99 37 (37.4) Printing Machine Operators(8921) 170 63 (37.1) Street Stall Salespersons and Vendors(5305) 79 29 (36.7) Welders(743) 335 122 (36.4) Cutters(7212) 68 23 (33.8) Interior Electricians(7622) 172 56 (32.6) Construction and Mining Related Managers(1411) 109 33 (30.3) Machine Tool Operators(851) 344 100 (29.1) Handling Equipment Operators(874) 239 69 (28.9) Korean Standard Classification of Occupation code (4 digit code) occupations with high SHS rates in our study. Tobacco effective way to reduce the SHS rate in the workplace smoke represents an occupational hazard and a and can be more effective if specifically designed for the smoke-free environment is an essential component of a various occupations and working styles in each country. healthy and safe. Smith and Leggat [15] reported that Particularly in South Korea, workers in their 40s and smoking rates were higher among unemployed persons 50s, workers employed in workplaces with less than 50 in many European countries like France, Italy, and employees, daily workers and temporary workers, Sweden, the United States and Australia, whereas in workers who work outside, and construction workers Japan, people who were currently employed actually had are priority target for non-smoking regulations at work. the higher smoking rates. These results can be affected Acknowledgements by different working condition including job status and The paper’s contents are solely the responsibility of the author and do not occupation of each country. Therefore it is necessary to necessarily represent the official vies of the OSHRI. analyze the smoking and SHS exposure rates in job status and occupation for each country. Funding Not applicable. The strength of this study is to analyze the SHS expos- ure by job status and occupations and identify the prior- Availability of data and materials ity group to implement smoking ban policy and confirm The present study used data from the 4th Korean Working Conditions Survey the workplace smoking is an occupational health hazard (KWCS), which was conducted between June and September 2014 on and a smoking ban policy at the workplace is the best employed workers, 15 years or older by the Occupational Safety and Health Research Institute (OSHRI) affiliated under the Ministry of Employment and option to reduce SHS. But, the limitation of study is that Labor. This data is open for anyone to use. in 4th KWCS data, participant’s smoking status was not surveyed and we have not been able to identify how Authors’ contributions much SHS exposure is affected by whether or not partic- HP analyzed research data, interpretated the result and written this paper, SC made conception and design of this paper and CL double-analyzed and ipants are smokers. re-checked the data analysis. All authors read and approved the final manuscript. Conclusions Tobacco smoke is a significant occupational hazard. Ethics approval and consent to participate Smoking cessation ban in the workplace can be a very Not applicable. Park et al. Annals of Occupational and Environmental Medicine (2019) 31:3 Page 9 of 9 Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 20 June 2018 Accepted: 17 January 2019 References 1. Jain RB. Exposure to second hand smoke at home and work among nonsmokers. Chemosphere. 2015;135:225–32. 2. National Health Statistics for 2015 (National Health Effects Survey, Phase 6, Third Year Data), Disease Control Headquarters. https://knhanes.cdc.go.kr/ knhanes/sub01/sub01_05.jsp#s5_01_01. Accessed 15 Aug 2018 3. OECD Data; Health at a glance (2017). https://data.oecd.org/healthrisk/daily- smokers.htm. Accessed 15 Aug 2018. 4. National Health Promotion Act, Article 9 (Date 31, Dec, 2011). https://elaw. klri.re.kr/eng_service/lawView.do?hseq=43278&lang=ENG. 5. Pickett MS, Schober ES, Brody DJ, Curtin LR, Giovino GA. Smoke-free laws and secondhand smoke exposure in US non-smoking adults, 1999–200. Tobacco Control. 2006;15(4):302–7. 6. State Smoking CDC. Restrictions for private-sector worksites, restaurants, and bars. Oncol Times. 2006;28(1):32–4. 7. Arheart KL, Lee DJ, Dietz NA, Wilkinson JD, Clark JD. Declining trends in serum cotinine levels in US worker groups: the power of policy. J Occup Environ Med. 2008;50(1):57–63. 8. Wortley PM, Caraballo RS, Pederson LL, Pechacek TF. Exposure to secondhand smoke in the workplace: serum cotinine by occupation. J Occup Environ Med. 2002;44(6):503–9. 9. Fischer F, Kraemer A. Factors associated with secondhand smoke exposure in different setting: results from the German health update(GEDA) 2012. BMC Public Health. 2016;16:327–36. 10. Howard J. Smoking is an occupational hazards. Am J Ind Med. 2004;46(2):161–9. 11. Verdonk-Kleinjan WM, Knibbe RA, Tan FE, Willemsen MC, de Groot HN, de Vries H. Does the workplace-smoking ban eliminate differences in risk for environmental tobacco smoke exposure at work? Health Policy. 2009;92(2–3):197–202. 12. Lee HS, Kim GH, Jung SW, Lee JH, Lee KJ, Kim JJ. The association between perceived discriminations and well-being in Korean employed workers: the 4th Korean working conditions survey. Ann Occup Environ Med. 2017;29:46. 13. Kim SJ, Lamichhane DK, Park SG, Lee BJ, Moon SH, Park SM, Jang HS, Kim HC. Association between second-hand smoke and psychological well-being amongst non-smoking wageworkers in Republic of Korea. Ann Occup Environ Med. 2016;28:49. 14. Bang KM, Kim JH. Prevalence of cigarette smoking by occupation and industry in the United States. American J Industrial Medicine. 2001;40:233–9. 15. Smith DR, Leggat PA. Tobacco Smoking by occupation in Australia; results from the 2004 to 2005 National Health Survey. J Occup Environ Med. 2007;49:437–45.

Journal

Annals of Occupational and Environmental Medicine – Springer Journals

Published: Jan 28, 2019

References

  • Exposure to second hand smoke at home and work among nonsmokers
    Jain, RB
  • Smoke-free laws and secondhand smoke exposure in US non-smoking adults, 1999–200
    Pickett, MS; Schober, ES; Brody, DJ; Curtin, LR; Giovino, GA
  • Restrictions for private-sector worksites, restaurants, and bars
    State Smoking, CDC
  • Declining trends in serum cotinine levels in US worker groups: the power of policy
    Arheart, KL; Lee, DJ; Dietz, NA; Wilkinson, JD; Clark, JD
  • Exposure to secondhand smoke in the workplace: serum cotinine by occupation
    Wortley, PM; Caraballo, RS; Pederson, LL; Pechacek, TF
  • Factors associated with secondhand smoke exposure in different setting: results from the German health update(GEDA) 2012
    Fischer, F; Kraemer, A
  • Smoking is an occupational hazards
    Howard, J
  • Does the workplace-smoking ban eliminate differences in risk for environmental tobacco smoke exposure at work?
    Verdonk-Kleinjan, WM; Knibbe, RA; Tan, FE; Willemsen, MC; Groot, HN; Vries, H
  • The association between perceived discriminations and well-being in Korean employed workers: the 4th Korean working conditions survey
    Lee, HS; Kim, GH; Jung, SW; Lee, JH; Lee, KJ; Kim, JJ
  • Association between second-hand smoke and psychological well-being amongst non-smoking wageworkers in Republic of Korea
    Kim, SJ; Lamichhane, DK; Park, SG; Lee, BJ; Moon, SH; Park, SM; Jang, HS; Kim, HC
  • Prevalence of cigarette smoking by occupation and industry in the United States
    Bang, KM; Kim, JH
  • Tobacco Smoking by occupation in Australia; results from the 2004 to 2005 National Health Survey
    Smith, DR; Leggat, PA